Digital sampling is a technique used to visualize a time-varying waveform by capturing quasi-instantaneous snapshots of the waveform via, for example, a sampling gate. The gate is “opened” and “closed” by narrow pulses (strobes) in a pulse train that exhibit a well-defined repetitive behavior such that ultimately all parts of the waveform are sampled. Currently, state-of-the-art real-time sampling can be used to capture a waveform record consisting of a complete sequence of successive data bits up to approximately 10 Gb/s by employing a very high speed analog-to-digital (A/D) converter (up to 40 G-samples/s). The advantage of real-time sampling is that it allows visualization of the exact characteristics of a data pattern that precedes a waveform error, such as slow risetime or excessive overshoot.
With equivalent-time sampling, the sampling rate can be arbitrarily low and the bandwidth of the oscilloscope is instead limited by the implementation of the sampling gate. However, equivalent-time sampling also requires the measured waveform to be repetitive—a fundamental limitation when compared to real-time sampling. The design of equivalent-time sampling devices is complicated, particularly with respect to determining the time-base corresponding to when each sample is acquired (since a hardware trigger with high precision is required). When using “equivalent-time sequential sampling”, the time-base (sweep) is generated by a hardware configuration using a trigger and a variable delay, thus determining when the next sample should be acquired. The delay is increased by a constant amount at each trigger event until the end of the sweep, and as a result the samples are acquired from each part of the waveform.
A common alternative time-base design is referred to as “equivalent-time random sampling”, in which the sampling rate is set by an internal clock that is independent of the signal repetition rate. For each trigger event in this design, a set of samples is acquired with constant time separation between the samples within a given set, with the next sampled set randomly shifted relative to the first set, as a function of the random relationship between the waveform trigger and the internal sampling clock. After several trigger events, the waveform is reconstructed.
More recently, efforts have gone into developing methods to calculate the sampling time-base directly from the samples acquired from the waveform. In particular, an algorithm is applied to a batch of samples acquired from the waveform being measured. The algorithm uses the spectral properties of the samples (by applying a Fourier transform) to find the relationship between the sampling rate and the waveform repetition frequency required to define the time-base of the sampled waveform. As a result, the sampling time-base can be determined without requiring a trigger signal. However, this technique has a few important drawbacks associated with the fact that no trigger signal is used. First, when a data signal is time-division-multiplexed (TDM) from a lower bit rate to a higher bit rate (such as, for example, from 10 Gb/s to 40 Gb/s), this prior art technique can only synchronize the samples relative to the higher bit rate (the sub-rate information thus being lost, with no way of distinguishing one channel from another). Additionally, waveform temporal drift relative to a trigger signal can no longer be visualized (where such drift tends to occur as a function of the optical transmission distance).
Thus, a need remains in the art for an arrangement capable of sampling high data rate pulses that utilizes a trigger signal (and thus retains the additional information mentioned above), but is not hampered in design by the conventional trigger signal requirements.